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Analyzing Emotional Trends from X Platform Using SenticNet: A Comparative Analysis with Cryptocurrency Price

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Abstract

This study investigates the relationship between emotional trends derived from X platform data and the market dynamics of prominent cryptocurrencies—Cardano, Binance, Fantom, Matic, and Ripple—during the period from October 2022 to March 2023. Utilizing SenticNet, key emotions such as fear and anxiety, rage and anger, grief and sadness, delight and pleasantness, enthusiasm and eagerness, and delight and joy were identified. The emotional data and cryptocurrency price data, sourced bi-weekly, were analyzed to uncover significant correlations. The findings reveal that emotions such as delight and pleasantness and delight and joy have the strongest positive correlations with Fantom’s price, while delight and pleasantness exhibit the strongest negative correlations with Cardano and Binance. The study highlights the nuanced impact of specific emotional states on cryptocurrency prices, offering valuable insights for market participants.

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Data Availability

No datasets were generated or analyzed during the current study.

Notes

  1. October second half.

  2. December second half.

  3. December first half.

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Acknowledgements

We express our gratitude to the SenticNet team for granting us unrestricted access to their resources.

Funding

The work was done with partial support from the Mexican Government through the grant A1-S-47854 of CONACYT, Mexico, grants 20232138, 20231567, and 20232080 of the Secretaría de Investigación y Posgrado of the Instituto Politécnico Nacional, Mexico. The authors thank the CONACYT for the computing resources brought to them through the Plataforma de Aprendizaje Profundo para Tecnologías del Lenguaje of the Laboratorio de Supercómputo of the INAOE, Mexico and acknowledge the support of Microsoft through the Microsoft Latin America PhD Award.

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Authors and Affiliations

  1. Instituto Politécnico Nacional (IPN), Centro de Investigación en Computación (CIC), Mexico City, Mexico

    Moein Shahiki Tash, Zahra Ahani, Olga Kolesnikova & Grigori Sidorov

  2. Entrepreneurship Department, Management and Economics Faculty, University of Sistan and Baluchestan, Zahedan, Iran

    Mohim Tash

Authors
  1. Moein Shahiki Tash
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  2. Zahra Ahani
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  4. Olga Kolesnikova
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  5. Grigori Sidorov
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Contributions

M.S.T., O.K., and Z.A. played pivotal roles in the experimental design and data collection, while M.S.T. and G.S. spearheaded the data analysis and interpretation. The initial manuscript was drafted by M.S.T. and O.K., with critical revisions contributed by Z.A., G.S., and M.T. All authors collectively approved the final manuscript. Notably, M.S.T., O.K., Z.A., G.S., and M.T. equally share authorship and take joint responsibility for the accuracy and integrity of the entire work.

Corresponding author

Correspondence to Olga Kolesnikova.

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Shahiki Tash, M., Ahani, Z., Tash, M. et al. Analyzing Emotional Trends from X Platform Using SenticNet: A Comparative Analysis with Cryptocurrency Price. Cogn Comput 16, 3168–3185 (2024). https://doi.org/10.1007/s12559-024-10335-8

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